Fig. 4: SpiB+ epithelial cells express more MHCII than SpiB-negative cells. | Nature Communications

Fig. 4: SpiB+ epithelial cells express more MHCII than SpiB-negative cells.

From: Lung structural cells are altered by influenza virus leading to rapid immune protection following re-challenge

Fig. 4

SpiB-mCherry reporter mice were infected with influenza A virus (IAV) (100-200PFU) and lungs taken at day 0, 10, or 30 post infection. EpCAM1+ epithelial cell populations were identified by gating on lineage (CD45, CD31, and CD140a) negative, SpiB negative or SpiB+ populations. A Frequency of SpiB positive or negative lung epithelial cells by cell subset in naive mice; the p values indicate that the population is present at a significantly greater percentage within the SpiB negative or positive subsets the color code is indicated in the figure. B Frequency of MHCII+ cells by each epithelial cell subset in naive mice. C Numbers of SpiB negative or positive populations at the different timepoints. D Percentage and E MFI of each population expressing MHCII at day 0, 10 and 30 post infection. In all experiments, data are combined with N = 11 naive, N = 7 primary, and N = 10 memory from two independent experiments. A Data show mean with SEM and differences tested by a one-way ANOVA and Šidák’s multiple comparison test with p values located in the group in which the cell type is present at a higher frequency. B–E each symbol represents a mouse and the bars show means with SEM error bars for normally distributed data and median with interquartile range for non-normally distributed data. B All data are normally distributed apart from Sca1+ progenitor cells. C All data are not normally distributed apart from Sca1 progenitor and Alveolar type (AT)II cells. D All data are normally distributed apart from Sca1 progenitor cells. E All data are not normally distributed apart from ciliated and club cells. B Normally distributed data are tested via paired t tests and non-normal by a paired Wilcoxon test. C, D normally distributed data are tested via a one-way ANOVA with a Šidák’s multiple comparison test and non-normal by a one-way Kruskal–Wallis test followed by a Dunn’s multiple comparisons test. Source data for all panels are provided as a Source Data file.

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